Get started

How to get started accessing, visualizing and processing data. The following instructions apply to the psana cluster.

From IPython

After logging into pslogin.slac.stanford.edu, add the following to your .bashrc file:

export PYTHONPATH="${PYTHONPATH}:/cds/sw/package/autosfx/btx"

Then from the terminal, activate a psana conda environment:

$ source /reg/g/psdm/etc/psconda.sh -py3

This permits loading modules directly in IPython, e.g.: from btx.interfaces.psana_interface import *

From JupyterHub

Alternatively, one can open a JupyterHub instance using the LCLS-I py3 kernel from https://pswww.slac.stanford.edu/. Running the following:

import sys
sys.path.append("/cds/sw/package/autosfx/btx")

enables the desired modules to be conveniently imported, e.g.: from psana_interface import *

Make sure you are running your scripts on the LCLS-I-py3 kernel.

Error message when starting the Jupyter hub

If this gives an error message, you will need to fix your ssh keys. Login to your account:

ssh myuserid@pslogin.slac.stanford.edu

and run the following line:

/cds/group/psdm/sw/jupyterhub/psjhub/jhub/generate-keys.sh 

Miscellaneous notes about the psana nodes and clusters

After logging into user@pslogin.slac.stanford.edu, one can access clusters including:

• DRP_FFB, the fast-feedback nodes. Access by ssh psffb, data at /cds/data/drpsrcf/{instrument}/{experiment}.
• PSDM, the data management cluster. Access by ssh psana, data at /cds/data/psdm/{instrument}/{experiment}.

NERSC remote analysis